Paper Citation Record · LEDGER

Superposition in Transformers: A Novel Way of Building Mixture of Experts

As of 11 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2501.00530.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.00530 v2

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:53:58.574061Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

21 of 21 outbound references displayed

verified exact0
verified fuzzy12
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a59730ed-cbb6-45ec-bf9e-6f1ad074e6f1 · outbound

This paper cites Language Models are Few-Shot Learners.

Superposition in Transformers: A Novel Way of Building Mixture of Experts Language Models are Few-Shot Learners

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T22:53:58.486206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ab48715-7ce4-420a-8e2e-ff68e93490c6 · outbound

This paper cites GPT-4 Technical Report.

Superposition in Transformers: A Novel Way of Building Mixture of Experts GPT-4 Technical Report

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T22:53:58.491852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f30da60-f181-4329-8299-7abd8871c122 · outbound

This paper cites McCloskey and N.

Superposition in Transformers: A Novel Way of Building Mixture of Experts McCloskey and N

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:53:59.122302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8d6bb2e5-be7d-4541-9a54-d0aceb65f815 · outbound

This paper cites Disentangling Neuron Representations with Concept Vectors.

Superposition in Transformers: A Novel Way of Building Mixture of Experts Disentangling Neuron Representations with Concept Vectors

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T22:53:58.501085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1fd2c4d1-739a-4519-833c-69e5242b974d · outbound

This paper cites Progressive Neural Networks.

Superposition in Transformers: A Novel Way of Building Mixture of Experts Progressive Neural Networks

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T22:53:58.506144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bafe454e-94e4-4458-b8e7-f664af9a432d · outbound

This paper cites Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran and Raia Hadsell.

Superposition in Transformers: A Novel Way of Building Mixture of Experts Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran and Raia Hadsell

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:53:59.108819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e3ed9d42-8e19-46a0-98e6-01481e4e3754 · outbound

This paper cites Jacobs, Michael I.

Superposition in Transformers: A Novel Way of Building Mixture of Experts Jacobs, Michael I

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:53:59.094350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 36391d15-130a-43f5-9d06-778fb95bc065 · outbound

This paper cites Outrageously large neural net- works: The sparsely-gated mixture-of-experts layer.

Superposition in Transformers: A Novel Way of Building Mixture of Experts Outrageously large neural net- works: The sparsely-gated mixture-of-experts layer

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:53:59.081255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e290c4bd-76cd-4b00-990c-532da986a089 · outbound

This paper cites Toward Inference-optimal Mixture-of-Expert Large Language Models.

Superposition in Transformers: A Novel Way of Building Mixture of Experts Toward Inference-optimal Mixture-of-Expert Large Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T22:53:58.523522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7eed3209-e674-4431-aa14-6f051f3da1df · outbound

This paper cites Parameter-efficient transfer learn- ing for NLP.

Superposition in Transformers: A Novel Way of Building Mixture of Experts Parameter-efficient transfer learn- ing for NLP

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:53:59.065120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7921e84d-92b2-4322-9b46-592c351d5ea8 · outbound

This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, and Weizhu Chen.

Superposition in Transformers: A Novel Way of Building Mixture of Experts Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, and Weizhu Chen

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:53:59.049324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c3757fa6-6ca7-48ff-8027-35d393a3a73c · outbound

This paper cites AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning.

Superposition in Transformers: A Novel Way of Building Mixture of Experts AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T22:53:58.535137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8853ec3-6d50-424d-bdb1-dad0cb6c816a · outbound

This paper cites Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning.

Superposition in Transformers: A Novel Way of Building Mixture of Experts Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T22:53:58.539289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 887ed76a-1e23-4718-a58f-6ce467f04336 · outbound

This paper cites Omni-SMoLA: Boosting Generalist Multimodal Models with Soft Mixture of Low-rank Experts.

Superposition in Transformers: A Novel Way of Building Mixture of Experts Omni-SMoLA: Boosting Generalist Multimodal Models with Soft Mixture of Low-rank Experts

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T22:53:58.543636Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb196863-f856-4015-8475-2d1b67528767 · outbound

This paper cites Toy Models of Superposition.

Superposition in Transformers: A Novel Way of Building Mixture of Experts Toy Models of Superposition

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T22:53:58.547524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fbf148f9-2614-41ef-a3db-95c46e18cc98 · outbound

This paper cites Zoom In: An Introduction to Circuits.

Superposition in Transformers: A Novel Way of Building Mixture of Experts Zoom In: An Introduction to Circuits

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:53:59.033911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 143f49b2-5b92-4fab-8f03-948729ca5547 · outbound

This paper cites Sparse autoencoders find highly interpretable features in language models.

Superposition in Transformers: A Novel Way of Building Mixture of Experts Sparse autoencoders find highly interpretable features in language models

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:53:59.019277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 278a7bb2-49a6-4501-88a7-cd392e5b9ac8 · outbound

This paper cites Towards Monosemanticity: Decomposing Language Mod- els With Dictionary Learning.

Superposition in Transformers: A Novel Way of Building Mixture of Experts Towards Monosemanticity: Decomposing Language Mod- els With Dictionary Learning

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:53:59.002746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 088cf15a-d8eb-4462-aef0-1627dd903fd3 · outbound

This paper cites Train big, then compress: Rethinking model size for efficient training and inference of transformers.

Superposition in Transformers: A Novel Way of Building Mixture of Experts Train big, then compress: Rethinking model size for efficient training and inference of transformers

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:53:58.986974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 24d2056b-fb7b-4c88-84e4-875ac88358fe · outbound

This paper cites Merging mod- els with fisher-weighted averaging.

Superposition in Transformers: A Novel Way of Building Mixture of Experts Merging mod- els with fisher-weighted averaging

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:53:58.973020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b7f0c151-ebff-4740-a708-cb77aa804619 · outbound

This paper cites Language Models are Unsupervised Multitask Learners.

Superposition in Transformers: A Novel Way of Building Mixture of Experts Language Models are Unsupervised Multitask Learners

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:53:58.958715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Pith citing papers

No inbound Pith citation observations are available.